app.py

# import os
# from dotenv import load_dotenv
# from groq import Groq
# import streamlit as st

# # Load environment variables
# load_dotenv()

# # Initialize the Groq client with API key
# client = Groq(api_key=os.getenv("GROQ_API_KEY"))

# # Function to generate MCQs based on the input text
# def generate_mcqs_from_text(user_text):
#     prompt = f"""
#     Based on the following text, generate between 30 to 50 multiple-choice questions. 
#     Each question should have four answer options, with one correct answer and three distractors. 
#     Make sure the questions are clear and test the user's understanding of the content. 
#     Provide the questions in the following format:
    
#     Question: [Your question here]  
#     A. [Option 1]  
#     B. [Option 2]  
#     C. [Option 3]  
#     D. [Option 4]  
#     Correct Answer: [Correct Option]
    
#     Text: {user_text}
#     """
#     chat_completion = client.chat.completions.create(
#         messages=[{"role": "user", "content": prompt}],
#         model="gemma2-9b-it",  # Use a valid model that supports chat completions
#     )
#     return chat_completion.choices[0].message.content

# # Function to evaluate user answers
# def evaluate_answers(mcqs, user_answers):
#     prompt = f"""
#     Here are the user's answers to the following multiple-choice questions. 
#     Please evaluate them as an experienced teacher, providing feedback on correctness, 
#     and explain why each answer is right or wrong.
    
#     MCQs: {mcqs}
#     User Answers: {user_answers}
#     """
#     chat_completion = client.chat.completions.create(
#         messages=[{"role": "user", "content": prompt}],
#         model="gemma2-9b-it",  # Use a valid model
#     )
#     return chat_completion.choices[0].message.content

# # Streamlit App
# st.title("Study Assistant - MCQ Generator & Evaluator")
# st.sidebar.header("Input Settings")

# # Input text from user
# user_text = st.sidebar.text_area("Enter the text for generating MCQs:", height=200)

# if st.sidebar.button("Generate MCQs"):
#     if user_text.strip():
#         with st.spinner("Generating MCQs..."):
#             mcqs = generate_mcqs_from_text(user_text)
#         st.subheader("Generated MCQs:")
#         st.text_area("MCQs", value=mcqs, height=400)
#         st.session_state["mcqs"] = mcqs  # Store MCQs for evaluation
#     else:
#         st.error("Please enter text for generating MCQs.")

# # Input user answers for evaluation
# if "mcqs" in st.session_state:
#     user_answers = st.text_area("Enter your answers (e.g., A, B, C, D for each question):", height=100)
#     if st.button("Evaluate Answers"):
#         if user_answers.strip():
#             with st.spinner("Evaluating answers..."):
#                 evaluation_result = evaluate_answers(st.session_state["mcqs"], user_answers)
#             st.subheader("Evaluation Result:")
#             st.text_area("Evaluation", value=evaluation_result, height=400)
#         else:
#             st.error("Please enter your answers for evaluation.")


import os
from dotenv import load_dotenv
from groq import Groq
import streamlit as st

# Load environment variables
load_dotenv()

# Initialize the Groq client with API key
client = Groq(api_key=os.getenv("GROQ_API_KEY"))

# Function to generate MCQs as a 35-year experienced educator
def generate_mcqs_from_text(user_text):
    prompt = f"""
    You are a 35-year experienced educator specializing in crafting challenging and insightful MCQs. 
    Based on the following text, generate between 30 to 50 multiple-choice questions (MCQs). 
    Each question should:
    1. Test critical thinking and understanding of the content.
    2. Include four options (A, B, C, D), with one correct answer and three well-designed distractors.
    3. Provide clear, concise language and avoid ambiguity.
    4. Provide the correct answer with each MCQ.

    Format the output as:
    Question: [Your question here]  
    A. [Option 1]  
    B. [Option 2]  
    C. [Option 3]  
    D. [Option 4]  
    Correct Answer: [Correct Option]
    
    Text: {user_text}
    """
    chat_completion = client.chat.completions.create(
        messages=[{"role": "user", "content": prompt}],
        model="gemma2-9b-it",  # Use a valid Groq-supported model
    )
    return chat_completion.choices[0].message.content

# Streamlit App
st.title("MCQ Generator with Correct Answers")
st.write("Paste your text below, and the app will generate MCQs with the correct answers.")

# Input text from user
user_text = st.text_area("Enter the text for generating MCQs:", height=200)

if st.button("Generate MCQs"):
    if user_text.strip():
        with st.spinner("Generating MCQs..."):
            mcqs = generate_mcqs_from_text(user_text)
        st.subheader("Generated MCQs with Correct Answers:")
        st.text_area("MCQs", value=mcqs, height=600)
    else:
        st.error("Please enter text for generating MCQs.")